Virtual Computing Environment for Future Combat Systems C om m anders N etw ork B attlefield Sim ulation N ationalA ssets,e.g. G rids, M aps,M odels Sensor N etw ork Shooters N etw ork V irtualdata grid M ulti-body Structures GIS V isualization V irtualPrototyping A pplicationsto FutureC om bat System s V C S Technologies
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Virtual Computing Environment for Future Combat Systems.
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Virtual Computing Environment for Future Combat Systems
Commanders Net work
Battlefield Simula tion
National Assets, e.g. Grids, Maps, Models
Sensor NetworkShooters Network
Virtual da ta grid
Multi-body Structures
GISVisualiza tion
Virtual Prototyping
Applications to Future Combat Systems
VCS Te chnologie s
HPGIS
Commanders Network e.g. Situation Assessment
National Assets, e.g. Maps
Sensor Network
Shooters Network
Maps are as important to soldiers as guns
Example Usage of Geographic Info. Systems (GIS) in Battlefield :
•Rescue of pilots after their planes went down (recently in Kosovo)
•Precision targeting e.g. avoid civilian casualities (e.g. friendly embassies)
•Logistics of Troop movements, avoid friendly fires
Motivating Example – Urban Warfare
Mogadishu, Somalia, 10/3/1993 Soldiers trapped by roadblocks No alternate evacuation routes Rescue team got lost in alleys having no planned route to crash site 18 Army Rangers and elite Delta Force soldiers killed, 73 wounded.
“Black Hawk Down”
( Mark Bowden, Black Hawk Down: A Story of Modern War )
• Components of the system• Gathering initial conditions
• Weather data from NWS or JSU • Terrain maps (State of federal Govt.)• Building geometry (City Govt.)
• Plume simulation using supercomputers• Visualizing results – map, 3D graphics• Response planning
• Q? What happens after plume simulation, visualization?
Homeland Defense: Chem-Bio Portfolio
Hurrican Andrew, 1992 Traffic congestions on all highways Great confusions and chaos
"We packed up Morgan City residents to evacuate in the a.m. on the day that Andrew hit coastal Louisiana, but in early afternoon the majority came back home. The traffic was so bad that they couldn't get through Lafayette."
- Morgan City, Louisiana Mayor Tim Mott
( http://i49south.com/hurricane.htm )
( National Weather Services)
( www.washingtonpost.com)
Problem Statement
Given• Transportation network (e.g. building floor map, city roadmap) with
capacity constraints• Initial number of people to be evacuated and their initial location • Evacuation destinations
Output• Scheduling of people to be evacuated and the routes to be taken
Objective• Minimize total time needed for evacuation• Minimize computational overhead
Constraints• Capacity constraints: evacuation plan meets capacity of the network
Route Algorithm - Related Works
• Dynamic network flow (Ford and Fulkerson, 1960’s)– Quickest Flow Problem: Only apply to single source and single destination node
• Simple algorithms for multiple source and destination (1970’s-1980’s)– Algorithms have exponential running time, e.g. EVACNET(University of Florida)
• Improved algorithms (1990’s)– Klinz:
• Polynomial time algorithm• Can only find required time, not the evacuation plan
– Tardos(1994): • Polynomial time algorithm to find optimal plan for fixed number of sources • Cannot apply to variable number of sources• Cannot apply to variable arc capacity, e.g. arc capacity changed over time• May produce fractional solution, e.g. “5.2 people go to …”,
feasible evacuation plan requires integer solution